Classification of Word Sense Disambiguation Errors Using a Clustering Method

DOI Web Site Web Site 5 References

Bibliographic Information

Other Title
  • クラスタリングを利用した語義曖昧性解消の誤り原因のタイプ分け
  • クラスタリング オ リヨウ シタ ゴギアイマイセイ カイショウ ノ アヤマリ ゲンイン ノ タイプ ワケ

Search this article

Abstract

As a first step of word sense disambiguation (WSD) errors analysis, generally we need investigate the causes of errors and classify them. For this purpose, seven analysts classified the error data for analysis from their unique standpoints. Next, we attempted to merge the results from the analyses. However, merging these results through discussions was difficult because the results differed significantly. Therefore, we used a clustering method for a certain level of automatic merger. Consequently, we classified WSD errors into nine types, and it turned out that the three main types of errors covers 90% of the total WSD errors. Moreover, we showed that the merged error types represented seven results and was standardized by defining the similarity between two classifications and comparing it with each analysis result.

Journal

References(5)*help

See more

Related Projects

See more

Keywords

Details 詳細情報について

Report a problem

Back to top